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Impacts of Climate Change on the Future of Biodiversity
Ecology Letters
Abstract
Ecology Letters (2012) 15 : 365–377
Abstract
Many studies in recent years have investigated the effects of climate change on the future of biodiversity. In this review, we first examine the different possible effects of climate change that can operate at individual, population, species, community, ecosystem and biome scales, notably showing that species can respond to climate change challenges by shifting their climatic niche along three non‐exclusive axes: time (e.g. phenology), space (e.g. range) and self (e.g. physiology). Then, we present the principal specificities and caveats of the most common approaches used to estimate future biodiversity at global and sub‐continental scales and we synthesise their results. Finally, we highlight several challenges for future research both in theoretical and applied realms. Overall, our review shows that current estimates are very variable, depending on the method, taxonomic group, biodiversity loss metrics, spatial scales and time periods considered. Yet, the majority of models indicate alarming consequences for biodiversity, with the worst‐case scenarios leading to extinction rates that would qualify as the sixth mass extinction in the history of the earth.
... Hoffmann 2021; Lai et al. 2022). If PAs do not incorporate climate change into their design-which is a common shortcoming-their effectiveness in preserving biodiversity may become compromised (Araújo et al. 2011;Bellard et al. 2012;S. Hoffmann et al. 2019;Mendez Angarita et al. 2023). ...
... Climate change does not always lead to species decline, as species may cope with new climatic conditions by altering their phenology, reproductive behavior, or ecology (Araújo et al. 2011;Bellard et al. 2012;S. Hoffmann et al. 2019;Mendez Angarita et al. 2023). ...
... When this is not possible, species need to shift their ranges to track their preferred climate. Terrestrial species are already moving poleward and/or toward higher elevations (Bellard et al. 2012;Hällfors et al. 2024;Scheffers et al. 2016; Thomas and Gillingham 2015), whereas aquatic species are moving deeper (Brito-Morales et al. 2020;Jorda et al. 2020). These shifts pose challenges for biodiversity conservation, particularly when PAs do not incorporate climate change considerations into their initial design or management strategies. ...
All ecosystems are affected by climate change, but differences in the pace of change will render some areas more exposed than others. Such spatial patterns of risk are important when assessing the continued functionality of protected area (PA) networks or planning for their expansion. Europe is undertaking an expansion of the PA network to cover 30% of its land and sea surface by 2030, but this must account for climate risk. Here, we estimate four metrics of future climate risk across Europe: local velocity, analog velocity, magnitude, and residence time, and assess the level of climate exposure of European PAs vs. nonprotected control sites. We also evaluate the intensity of climate risks on > 1000 European species of conservation concern associated with Natura 2000 sites. Our results show large spatial differences in climate change exposure across Europe, with a faster pace and farther shifts in the Boreal, Steppic, and Pannonian regions but slower changes in the Mediterranean, Alpine, Arctic, and Macaronesia regions. The magnitude of climate change was higher for the Arctic, Alpine, and Mediterranean regions, implying large local differences between present and future climate. These spatial risk patterns were largely consistent across scenarios, but with up to three times higher risk under the most pessimistic vs. the most optimistic scenario. Large variation in climate exposure for species of conservation concern was revealed, including 11 species that are highly dependent on Natura 2000 sites and predicted to experience rapid climate change. Our results provide guidance for managing European PAs and expanding their coverage by pinpointing areas offering more stable climates. We emphasize the need for connectivity across the network to support species adaptation via range shifting. This is especially the case in areas facing high climate change magnitude but low velocity, implying that climate conditions similar to current ones will be found nearby.
... Predicting changes in biodiversity has become an extremely important aspect of climate change research over the last two decades. Many predictive studies suggest that climate change will have a major impact on all levels of diversity, from organisms to biomes (Bellard et al., 2012). Ecosystems with high species diversity are more stable under interannual climate variability, but the pattern of biodiversity-stability relationships under extreme climate conditions is not yet fully understood (De Boeck et al., 2018). ...
... Short-term global warming can have a major impact on the functional structure of grassland communities, both in terms of trait dominance and functional diversity (Debouk et al., 2015). For example, plants may respond to climate warming by changing their phenology, geographic range and physiology, including dispersal and reproduction (Bellard et al., 2012). Warmer temperatures can increase the dominance of species with a higher specific leaf area (SLA), thus increasing the proportion of fast-growing species (Debouk et al., 2015). ...
Grasslands are an integral part of terrestrial land cover being highly biodiverse, semi-natural habitats. With the decline of this ecosystem due to direct human impacts, remaining grasslands are under increasing pressure from climate change. Thus, the main objective of our research was to determine the taxonomic and functional responses in grasslands under the influence of simulated extreme inundation and climate warming. The field experiment was conducted on translocated grassland plots in the Radzionków Botanical Garden. We analysed the response of vegetation with the use of plant functional trait changes related to persistence, growth rate, reproduction and competitive ability (specific leaf area, SLA; leaf dry matter content, LDMC; height; seed mass) and plant life strategies (C, S, R) using trait-based approach (community weighted means and functional diversity indices). The results showed increased temperature caused a significant increase in competitiveness (C strategy) for all species and for the forb group counted separately, and a decrease in the ruderal strategy for the forb group. We found that the higher the hydration, the lower the species richness (more so at higher temperatures). In addition, we find that drought increases functional richness, mainly due to an increase in SLA and a higher proportion of forbs. Furthermore, warming decreases functional richness of graminoids and increases functional divergence of graminoids and forbs, especially in dry conditions. Our research indicates that climate change has a complex impact on plant diversity in European grasslands, highlighting the need for further exploration of these interactions to predict long-term effects on biodiversity and ecosystem functioning.
... Tushar & Rahman (2023), together with similar studies, demonstrate how solar energy systems adoption impacts long-term investment portfolios according to their research. MIC-MAC frameworks integrated with externalities from a changing climate would give investors deeper sensitivity insight about long-term outcomes according to Bellard et al. (2012), Brook et al. (2008). ...
... Rao & Singh, 2023).Diagram 2: The monitoring of driving cluster variables should be continuous because they demonstrate high driving power yet low dependence Market liquidity together with investor sentiment remain important factors, yet they tend to respond after macroeconomic elements such as interest rate adjustments or financial policy changes. The policymakers along with financial institutions need to adopt transparent and consistent economic policies according toBellard et al. (2012) which builds investor trust and lessens sudden market shifts. Application of ISM-MICMAC for Investment DecisionsThis research used ISM alongside MIC-MAC to establish an organized framework between the various variables and their connection strengths. ...
Investment sensitivity refers to the responsiveness of investment decisions to various internal and
external influencing factors, including market dynamics, policy changes, technological
advancements, and investor behavior. In the modern financial landscape, characterized by
volatility and complexity, identifying and structuring these factors is crucial for robust investment
strategies. This paper employs the MIC-MAC structural modeling approach to analyze and classify
the interdependencies among factors affecting investment sensitivity. By integrating Interpretive
Structural Modeling (ISM) with the MIC-MAC technique, the study reveals a hierarchical
structure and categorization of key drivers based on their driving and dependence power. The
analysis is enriched through expert validation and a focused application scenario, offering insights
into strategic decision-making, investment risk management, and policy formulation. The paper
also incorporates graphical models, flowcharts, and pseudo-code representations to enhance clarity
and applicability for both academic and professional financial environments. The results provide
a structured decision-making framework for stakeholders navigating uncertain investment
climates.
Keywords: Investment Sensitivity, MIC-MAC Analysis, Interpretive Structural Modeling (ISM),
Decision-Making, Financial Modeling, Risk Analysis, Structural Modeling
... However, biodiversity faces severe threats from habitat destruction, pollution, overexploitation, and climate change (Pimm et al., 2014). Rising global temperatures and shifting climatic conditions disrupt species distributions and ecosystem dynamics, increasing extinction risks (Bellard et al., 2012). Coral reefs, highly sensitive to temperature changes, are experiencing widespread bleaching, imperiling marine biodiversity (IPCC, 2022). ...
... Climate change is anticipated to have various impacts on biodiversity, influencing species and ecosystems in multiple ways (Parmesan, 2006). It is expected to become one of the primary drivers of the decline in African biodiversity over the next century (Sala et al., 2000;Bellard et al., 2012;Midgley & Bond, 2015). ...
... A major response of species to climate change is the shifting of their distributions to track suitable abiotic conditions (Parmesan and Yohe 2003;Bellard et al. 2012), particularly in marine environments where organisms face fewer obstacles to their dispersion than on land (Poloczanska et al. 2014;Lenoir et al. 2020;Pinsky et al. 2020). Modelling future distribution shifts under climate change scenarios is a common approach to predict the impacts of climate change and derive future biodiversity distribution patterns. ...
To predict the spatial responses of biodiversity to climate change, studies typically rely on species‐specific approaches, such as species distribution models. In this study, we propose an alternative methodology that investigates the collective response of species groups by modelling biogeographical regions. Biogeographical regions are areas defined by homogeneous species compositions and separated by barriers to dispersal. When climate acts as such a barrier, species within the same region are expected to respond similar to changing climatic conditions, enabling the prediction of entire region shifts in response to future climate scenarios. We applied this approach to the Southern Ocean, which exhibits sharp climatic transitions known as oceanic fronts, focusing on the mesopelagic lanternfishes (family Myctophidae). We compiled occurrence data for 115 lanternfish species from 1950 onwards and employed a network‐based analysis to identify two major biogeographical regions: a southern and a subtropical region. These regions were found to be distinct, with minimal overlap in species distributions along the temperature gradient and a separation around 8°C, indicating that temperature likely acts as a climatic barrier. Using an ensemble modelling approach, we projected the response of these regions to future temperature changes under various climate scenarios. Our results suggest a circumpolar expansion of the subtropical region and a contraction of the southern region, with the Southern Ocean becoming a cul‐de‐sac for southern species. Ultimately, our results suggest that when support is found for the climatic barrier hypothesis, community‐level models from a ‘group first, then predict’ strategy may effectively predict future shifts in species assemblages.
... Understanding how populations respond to environmental changes is essential for effective conservation. For instance, changes in range, immigration or dispersion rates and life-history traits in response to environmental changes can affect population growth and persistence (Bellard et al., 2012;Doak & Morris, 2010;Parmesan & Yohe, 2003). In particular, changes in population growth in response to environmental changes can be mediated by phenotypic changes through different mechanisms: changes in demographic structure, phenotypic plasticity and contemporary evolution (Chevin et al., 2012;Gonzalez et al., 2013;van Benthem et al., 2017). ...
Demographic and evolutionary modelling approaches are critical to understanding and projecting species responses to global environmental changes. Population matrix models have been a favoured tool in demography, but until recently, they failed to account for short‐term evolutionary changes. Evolutionary‐explicit demographic models remain computationally intensive, difficult to use and have yet to be widely adopted for empirical studies. Researchers focusing on short‐term evolution often favour individual‐based simulations, which are more flexible but less transferable and computationally efficient. Limited communication between fields has led to differing perspectives on key issues, such as how life‐history traits affect adaptation to environmental change.
We develop a new EvoDemo hyperstate matrix population model (EvoDemo‐Hyper MPM) that incorporates the genetic inheritance of quantitative traits, enabling fast computation of evolutionary and demographic dynamics. We evaluate EvoDemo‐Hyper MPM against individual‐based simulations and provide analytical approximations for adaptation rates across six distinct scales in response to selection. We show that different methods yield equivalent results for the same biological scenario, although semantic differences between fields may obscure these similarities.
Our results demonstrate that EvoDemo‐Hyper MPM provides accurate, computationally efficient solutions, closely matching outcomes from individual‐based simulations and analytical approximations under similar biological conditions. Adaptation rates per generation remain constant across species when selection acts on fertility but vary with other vital rates. Adaptation per time decreases with generation time unless selection targets adult survival, where intermediate life histories adapt fastest. Rates per generation, defined as the relative change in individual fitness, remain constant across species and vital rates.
We discuss that no general prediction emerges about which species or life‐history traits yield higher adaptation rates, as outcomes depend on life cycles, vital rates and the definition used. We provide Matlab and R code to support the application of our EvoDemo‐Hyper MPM.
... Species diversity (SD) and genetic diversity (GD) within species are the main targets of conservation worldwide, threatened by ongoing anthropogenic climate change and habitat degradation (Bellard et al. 2012;Pauls et al. 2013). However, estimating GD for many species requires large efforts in terms of sampling and investment in genetic analyses, which are rarely possible. ...
Aim
It has been proposed that species diversity (SD) and genetic diversity (GD) co‐vary across natural communities because both are shaped by processes such as immigration and drift. However, empirical reports are contradictory, and multispecies studies are rare. Here we test the hypothesis that the two diversity measures do not correlate in systems with high levels of immigration stochasticity and little GD caused by strong genetic drift.
Location
Tropical alpine habitats on six of the highest mountains in eastern Africa.
Taxon
Vascular plants.
Methods
We sampled 375 taxa in 75 plots in five habitat types, recorded ecological variables, and genotyped 1793 plants representing 20 species/species complexes.
Results
We confirmed that intrapopulation GD was exceptionally low in this system and found that most Species‐Genetic Diversity Correlations (SGDCs) were weak and insignificant. Whereas SD was correlated with several environmental variables, GD was only correlated with mountain identity (geographical location) and mountain age.
Main Conclusions
Our findings support the hypothesis that SGDCs are lacking in habitat island systems such as the tropical alpine region in Africa, which is characterised by frequent population size fluctuations, extinctions, and colonisations via long‐distance dispersal (LDD) during the glacial cycles. The stochastic nature of LDD combined with strong genetic drift and founder effects is likely to cause low GD and lack of SGDCs, implying that SD cannot be used as a proxy for GD in conservation management of such systems.
... Species distribution models (SDMs) are widely used tools to study past, present and future species distribution (Bellard et al., 2012;Cheung et al., 2009). They allow the statistical estimation of species occurrence or abundance in unsampled areas or under future climate conditions, assuming that environmental factors influence species distribution (Guisan and Zimmermann, 2000). ...
Species Distribution Models (SDMs) are widely used tools for studying potential climate-induced shifts in species distribution to support future marine spatial planning. However, the ecological plausibility of selected models is often neglected, particularly in marine ecosystems, resulting in potentially misleading outcomes, especially when climate effects are of concern. In this study we modeled the distribution of 11 commercial fish species in the North Sea using 57 years of observations and 60 SDMs with various degrees of freedom and aimed to improve the ecological plausibility of SDMs by evaluating common model selection techniques. Model performance was evaluated using deviances obtained with three cross-validation designs, Akaike Information Criterion, median absolute deviation and percentage of local mismatch. We identified top performing models based on consistent good scores of those metrics and assessed the ecological plausibility of all models. Specifically, we tested whether the modeled temperature response curve aligned with the ecological niche concept, i.e. having a bell shape within the plausible temperature range for each species, where the highest habitat suitability should relate to optimal conditions. The tested performance metrics often yielded conflicting outcomes and selected models with implausible temperature response curves that had poor extrapolation skills in temperature space and, thus, may result in unreliable predictions under climate change. Building on our findings, we provide recommendations for future SDM applications to improve their accuracy, ecological plausibility and predictive skills in climate-related studies.
... Climate change poses significant threats to wetland ecosystems, requiring collective global efforts to [33][34][35][36][37] . ...
Climate change has had extensive impacts on wetland ecosystems on Earth, posing a significant threat to the survival and services provided by these ecosystems. This paper aims to comprehensively assess the effects of climate change on wetland ecology, discuss adaptive strategies for wetland ecosystems, and identify future research directions. The paper begins by introducing the definition and ecological foundations of wetlands, emphasizing their crucial role in the global ecosystem. Subsequently, it delves into the multifaceted impacts of climate change on wetlands, encompassing aspects such as rising temperatures, changes in precipitation patterns, sea-level rise, and frequent extreme weather events. Adaptive strategies for wetland ecosystems include biodiversity maintenance, habitat restoration, and artificial interventions. In conclusion, the paper looks ahead to the future, highlighting challenges such as the uncertainty of climate change and the long-term responses of ecosystems.
... Climate change, characterized by rising global temperatures, constitutes a significant threat to all life forms (Bellard et al. 2012). Projections indicate a global average temperature increase of 1 to 3 °C until the end of the twenty-first century (Portner et al. 2022). ...
Screening of pollen traits in diploid wild potatoes (Solanum sect. Petota, Solanaceae) is desirable to develop heat-tolerant potato (S. tuberosum) cultivars. Accomplishing this goal requires exploring potato genetic resources that are conserved in genebanks. The goal of this study was to assess pollen viability and 2n pollen production of diploid potato wild relatives under heat stress conditions. We assessed pollen viability and size of nine potato accessions conserved at the Embrapa Potato Gene Bank, including eight wild potatoes: S. chacoense (BRA 00167447–2, BRA 00167017–3, BRA 00167023–1, BRA 00167028–0), S. commersonii (BRA 00167007–4, BRA 00167420–9, BRA 00183760–8), and S. malmeanum (BRA 00183755–8), along with a control accession from the cultivated species S. tuberosum (BRA 00167251–8). The plant accessions were cultivated in separate growth chambers, subjected to both control temperature (ranging from 14 to 27 °C) and supraoptimal temperature conditions (ranging from 24 to 34 °C). At heat stress, the accession BRA 00167251–8 did not bloom, and BRA 00167023–1 did not produce pollen. The remaining accessions did not exhibit a significant reduction in pollen viability as the temperature increased. Pollen viability at the control temperature had the lowest value in BRA 00167420–9 (S. commersonii) with 68.5% and the highest in BRA 00183755–8 (S. malmeanum) with 100%. At the supraoptimal temperature, the lowest value was in BRA 00167420–9 (S. commersonii) with 54.5% and the highest in BRA 00167017–3 (S. chacoense) with 94%. The average pollen diameter was 20 µm in all wild potato genotypes, and the increase in temperature did not lead to 2n pollen production. Estimated genotypic coefficient of variation (GCV) was lower than phenotypic coefficient of variation (PCV) for pollen viability. The observed heritability ranged from 58.8% in BRA 00167007–4 to 91.3% in BRA 00183755–8. Our results highlight the genetic variability available in wild potato germplasm concerning pollen viability under heat stress. Furthermore, these first insights offer valuable guidance for ongoing and future endeavours in diploid potato breeding.
... Therefore, the capacity of mobile organisms to respond to land-use gradients should depend largely on their dispersal ability, and on how specialized their requirements are for environmental conditions necessary for growth, survival and reproduction (Tscharntke et al. 2005, Devictor et al. 2008, Williams et al. 2010. Similarly, the response of organisms to changes in climate depend on an individual's characteristics (Bellard et al. 2012); organisms with narrower physiological tolerances, lower dispersal ability, and that depend on specialized habitats, resources and interspecific interactions are also expected to be more sensitive and have a lower adaptive capacity to a changing climate (Foden et al. 2013). Determining how different groups of organisms respond to combined effects of changing land use and climate is therefore essential to be able to predict which groups could be more vulnerable in future environmental conditions (Kujala et al. 2013, Robillard et al. 2015, Williams and Newbold 2020. ...
Land‐use changes and climatic changes are two entwined stressors on ecosystems. Studies on such interactions often focus on species‐level or region‐specific responses, but fewer have examined differences in responses based on functional traits. Here we examine the influence of natural habitat cover and temperature change on the abundance of all arthropods and on the abundance of pollinator, pest and natural enemy trait syndromes (based on diet breadth, habitat breadth and dispersal mode) in arthropod communities within European agroecosystems. Using a previously compiled dataset along with historical climatic data, we found that all arthropods, diet generalist pollinators and habitat generalist pests were more abundant in sites with a high amount of natural habitat regardless of temperature changes experienced. For diet specialist pollinators, natural habitat and temperature change antagonistically influenced abundance; high amounts of natural habitat in landscapes appeared to mitigate the negative effects of increasing temperature extremes. Habitat specialist pest abundance was higher in sites that experienced greater increases in mean annual temperature, regardless of natural habitat cover. Natural enemies appeared to be more abundant in sites that experienced greater increases in temperature variation. For natural enemies that were flight‐dispersing and habitat generalists this was regardless of natural habitat cover, while for ground‐dispersing natural enemies, temperature change and high natural habitat cover appeared to benefit habitat generalists (ground beetles) and specialists (primarily spiders). Given the variability in responses we observed between different arthropods based on diet breadth, habitat specialism, dispersal ability and functional group, we conclude that functional approaches examining impacts of qualitatively different stressors can help inform future conservation actions or mitigation efforts.
... Biodiversity is currently facing an unprecedented crisis, with species across the globe endangered by a variety of human activities (Cardinale et al., 2012;McCauley et al., 2015). These challenges are further intensified by climate change, which exacerbates existing threats and poses new risks to vulnerable species and ecosystems (Bellard et al., 2012;Dirzo et al., 2014;Malhi et al., 2020). Aquatic ecosystems, which are among the most vulnerable to these changes, experience a more pronounced decline in functioning and alterations in species richness (Forster et al., 2012). ...
Anthropogenic changes in global aquatic biodiversity necessitate the urgent adoption of more efficient bio-monitoring approaches. Environmental DNA (eDNA) metabarcoding has emerged as a powerful tool that has enhanced the field of biomonitoring. However, the efficiency of eDNA detection can be hindered by various environmental and methodological factors. This is an area of active research that has not yet been fully crystallized , especially on a large scale where variations in environmental factors might unmask further intricacies. Here, we aimed to investigate the impact of key environmental factors across broad biogeographical areas on eDNA detection and explore how methodological variations in eDNA-based biomonitoring might influence detection outcomes-through a synthesis study conducted under real-world conditions. To address this, we performed a literature search and compiled a dataset from 22 studies of species occurrence from both eDNA and traditional approaches. We examined the effects of temperature, UV, salinity, filter pore size, and DNA fragment length on eDNA detection probability-defined as the likelihood of detecting species through eDNA relative to the total number of species detected by both approaches. The results revealed that temperature, independently and in combination with UV, consistently reduced eDNA detection, meaning that eDNA detection fell in hotter locations and seasons with more intense UV exposure. Similarly, salinity exerts a slight negative impact, whereas filter pore size and DNA fragment size show no effect. Our findings highlight the intricate spatial-temporal effects of environmental factors on eDNA detection efficacy, emphasizing the need to consider them in the execution of eDNA studies.
... These areas harbour the majority of the world's plant species, including exceptionally high concentrations of endemic, rare, and threatened taxa. However, biodiversity hotspots are increasingly vulnerable to the impacts of human-induced climate and land-use change (Bellard et al., 2012(Bellard et al., , 2014Enquist et al., 2019;Habel et al., 2019). As a result, plant species extinctions have reached unprecedented levels in human history , despite the inherent resilience of plants to extinction and their typically long extinction lag times (Cronk, 2016). ...
In the Anthropocene, conservation planning must adapt to rapid environmental changes driving the global biodiversity crisis. The impacts of climate and land-use change are particularly severe in biodiversity hotspots like the Mediterranean Basin, where unique taxa and ecosystems are increasingly at risk. To address these challenges, we conducted a forward-looking conservation gap analysis in Peloponnese, Greece, a regional endemism centre and key component of the Mediterranean biodiversity hotspot, providing a case study to support the development of cost-effective conservation strategies. We applied a taxonomically and phyloge-netically informed approach to identify endemism hotspots across different time-periods. Persistent hotspots were mapped under future climate and land-use scenarios, and their overlap with protected and roadless areas was assessed. Our analysis revealed that endemism hotspots will likely shift geographically and diminish in extent over the coming decades. While key mountainous regions are expected to retain their hotspot status, our results point to a widespread decline in endemism and overall biodiversity loss. Concerningly, the most critical persistent hotspots overlap with extinction risk hotspots. Moreover, up to 46 % of the persistent endemism hotspots are not covered by designated protected areas, and <8 % of those lie within roadless areas. Our results highlight the need for a coordinated multi-dimensional strategy that should include the expansion of the current network of protected areas, the establishment of plant micro-reserves, and the translocation and reinforcement of populations of endemics. The identified conservation gaps represent regions of enduring resilience to environmental change, making them critical targets for long-term conservation planning.
... This, in turn, contributes to an increase in EMF (Felton et al. 2020;Hu et al. 2022). However, variations in soil moisture resulting from altered precipitation affect the composition and structure of biological communities, and the cascade effects between multi-trophic levels, thereby regulating EMF (Bellard et al. 2012;Soliveres et al. 2016;Wagg et al. 2014). Furthermore, our findings indicated that when combining direct and indirect effects, ...
Aims
Dryland ecosystems are susceptible to variations in precipitation. Biodiversity plays a vital role in regulating ecosystem functions. However, the effects of altered precipitation on plant and soil microbial diversity and their relationship with ecosystem multifunctionality (EMF) in desert steppes remain unclear.
Methods
We conducted a three–year precipitation manipulation experiment in a desert steppe in northwestern China to evaluate how altered precipitation influences plant and microbial diversity, EMF, and individual ecosystem functions.
Results
R33 significantly decreased the Shannon and Pielou indices of plant, as well as EF–GP and EF–P. R66 significantly decreased EMF, EF–GP, EF–N, and EF–P. In contrast, only R166 significantly decreased the Pielou index of plant. There were significant interannual variations in plant diversity, microbial diversity, EMF, and single functions. The interaction between precipitation and year significantly affected only plant diversity, microbial diversity, and EF–GP. The multi–threshold approach indicated that ecosystem functions were positively correlated with plant and fungal diversity and negatively correlated with bacterial diversity under altered precipitation. Additionally, the structural equation model demonstrated that precipitation regulated EMF by affecting plant and microbial diversity through changes in soil water content. Compared with plant diversity, microbial diversity was more significant in regulating the response of EMF to altered precipitation.
Conclusions
This study demonstrates that plant and microbial diversity jointly regulate ecosystem functions under altered precipitation, but microbial diversity plays a more prominent role. Therefore, the importance of microbial communities should be given particular attention when predicting and managing the response of dryland ecosystems to future climate–induced precipitation changes.
... For example, adaptations cause mismatches in symbiotic relationships, such as in plant and pollinator species (Rafferty and Ives 2011). Other ecological relationships between competitors and prey/predators are largely damaged as species and populations must migrate or decline (Yang and Rudolf 2010;Bellard et al. 2012) (Fig. 17.1). ...
Global epidemiological studies have revealed that climate change has led to a decrease in biodiversity and has been responsible for the pollution of air, water, and food, including the presence of microplastics. These factors have contributed to the rise of various non-communicable diseases (NCDs). As a result, the overall expenses related to healthcare, work productivity, mental health, and the economic situation of nations, particularly those with limited resources, have been adversely affected. The human exposome, epithelial barriers, microbiome and immune system are all affected leading to an impact on immune health. These have led to a higher prevalence of NCDs such as diabetes, arthritis, cardiovascular diseases, obesity, cancer, asthma and allergies. Vulnerable and underserved populations such as children, pregnant women, migrants those with underlying disease, the elderly and indigenous people are particularly burdened by the health effects of climate change. Wild and domestic animals and food chains are also severely affected by the same factors. One Health is an interdisciplinary approach calling for collaborative efforts of working locally, nationally, and globally, to attain optimal health for people, animals and our environment because of their interconnectedness. To reverse planetary degradation, achieve sustainability and reduce the risk of potential disease outbreaks a multidisciplinary, cross-sector, and transborder approach under G20’s leadership to change practices and policies at every level, from global to local is needed.
... Overall, the combination of heat and drought can lead to high yield losses, depending on the severity and timing of the stress [19][20][21]. Agricultural production is expected to be most affected by climate change, particularly in low-latitude regions where developing nations are concentrated [22]. The negative consequences of rising carbon dioxide and high temperatures will compel researchers to develop effective adaptation strategies [23]. ...
Maize (Zea mays L.) is a staple cereal crop worldwide, but its productivity is significantly affected by extreme weather conditions such as drought and heat stress. Plant growth, physiological processes, and yield potential are all affected by these conditions; as such, resilient maize crops are required to tackle these abiotic challenges. With an emphasis on morphological, physiological, and biochemical reactions, this review paper investigates the processes that underlie resistance to certain environmental challenges. Features including deep root systems, osmotic adaptations, and antioxidant enzyme activity help maize withstand drought. Activation of drought- and heat-responsive genes, accumulation of osmoregulatory compounds, and changes in membrane fluidity are all components of abiotic stress tolerance. Likewise, improved transpiration efficiency, modified photosynthetic processes, and improved heat shock proteins are used to produce heat resistance. Enhancing resilience requires progress in breeding methods, genetic engineering, and agronomic techniques, such as the use of stress-tolerant cultivars, biotechnology interventions, and climate-smart agriculture tactics. A special focus was given to cutting edge technologies like CRISPER-Cas9-mediated recent advances in heat and drought resistance. This review sheds light on recent studies and potential avenues for enhancing resilience to harsh climatic conditions, guaranteeing food security in the face of climate change.
... and Roques 2010; Couet et al. 2022). Species unable to adapt to these changes may attempt migration; however, if they cannot disperse, they face the grim prospect of local or global extinction (Thuiller et al. 2008;Bellard et al. 2012). Climate change can induce shifts in species range at various scales, affecting both individual populations and ecosystems (Karl et al. 2009). ...
Climate change, a global threat of utmost significance, has the potential to trigger shifts in biodiversity distribution and the emergence of novel ecological communities. While considerable research has focused on predicting the impacts of climate change on the range shift of species, a critical yet often overlooked aspect is the role of changing climate on plants in hot, arid, and poorly known ecosystems. We employed an ensemble species distribution modeling framework to investigate how climate change might affect the spatial range of two significant indicator species, Ziziphus spina‐christi and Ziziphus nummularia, within the hot and arid Khalijo‐Omanian ecosystem of Iran. We ran the models for the current species distribution using climatic variables and then projected the models for two future periods (2041–2070 and 2071–2100) under different climate scenarios. These findings suggest that both species respond differently to climate change under different climatic scenarios. Some regions may undergo range expansion, whereas others may experience range contraction due to shifting environmental conditions. Overall, both species are projected to shift their range towards higher latitudes as climatic conditions evolve. Conservation and management measures, including the identification of priority areas, are crucial for protecting these species. The conclusions of this study are valuable to biodiversity conservation authorities, local stakeholders, and individuals dedicated to preserving Ziziphus habitats.
... Climate change caused by human activities poses a profound threat to global biodiversity (Bellard et al., 2012). Alterations in temperature and precipitation are expected to affect species distribution ranges (Pecl et al., 2017), modify regional species composition and structure, and lead to spatial and temporal variations in biodiversity patterns (Thuiller et al., 2011;Scheffers et al., 2016). ...
Over the past century, anthropogenic greenhouse gas emissions have continuously increased global temperatures and triggered climate change, significantly impacting species distributions and biodiversity patterns. Understanding how climate-driven shifts in species distributions reshape diversity patterns is crucial for formulating effective future conservation strategies. Based on the distribution data of 314 Rhododendron species in China, along with 16 environmental variables, we examined spatial diversity patterns and assessed regional and biome differences in species responses using ensembled species distribution models. Our results indicated that climatic variables significantly influenced species distributions, with ongoing climate change expected to concentrate Rhododendron distribution patterns and alter species composition. Regional topography played a critical role in shaping species responses to warming. In the mountainous areas of southwestern China, species exhibited heightened sensitivity to temperature fluctuations, shifting upward as temperature increased. This region also had a higher proportion of threatened species and showed an overall contraction in primary distribution range. Conversely, in southern China, species were more influenced by precipitation, exhibiting a notable northward shift and expansion in primary distribution areas. Notably, alpine species, occurring in habitats above the treeline, may face severe survival risks due to the high degree of habitat loss and fragmentation. We identified seven priority conservation areas, predominantly situated in highly fragmented mountainous regions that were inadequately protected by existing nature reserves. Our findings contribute to a better understanding of changes in Rhododendron diversity patterns under climate change, providing valuable insights for developing comprehensive, flora-wide conservation plans in China.
... The impact of heatwaves on planktonic organisms may be exacerbated under future environmental conditions if warming, increasing pCO 2 , or changes in nutrient availability already push planktonic organisms toward the edge of their tolerance windows. Given that global change impacts plankton biodiversity (Bellard et al. 2012) and community composition and biomass (Greve et al. 2004;Telesh et al. 1999) may, in turn, alter energy transfer to higher trophic levels and nutrient recycling, there is an urgent need for studies addressing the combined effects of short-and long-term environmental changes on planktonic food webs. ...
In the context of global change, marine organisms are subjected not only to gradual changes in abiotic parameters, but also to an increasing number of extreme events, such as heatwaves. However, we still know little about the influence of heatwaves on the structure of marine communities, and experimental studies are needed to test the impact of heatwaves alone and in combination with other environmental drivers. Here, we conducted a mesocosm experiment to assess the potential impact of heatwaves on plankton communities, which we did under ambient and future environmental conditions. To simulate future environmental conditions, we simultaneously manipulated temperature and pH based on IPCC predictions for 2100, and dissolved N : P ratios based on the conditions expected in European coastal zones. While we did not observe any effects of simulated heatwaves on phytoplankton abundances, we identified that future environmental conditions may favor smaller phytoplankton species and that additional heatwaves may especially favor small phytoflagellates and coccolithophores. We also observed that future environmental conditions may reduce the abundances and modify the species composition of bacterioplankton, microzooplankton, and mesozooplankton, and that heatwaves may exacerbate these effects. Using a unique approach to examine the potential impacts of heatwaves under current and future environmental conditions on a natural multi‐trophic marine plankton community, we show that the combination of multiple global change drivers has the potential to perturb the entire basis of marine food webs.
... The IRB's position in this drought-prone, fragile ecosystem zone, combined with its complex transnational governance structure, makes it an exemplary and urgent case for investigating how wetland landscape changes impact carbon sequestration capacity. Understanding these dynamics within the IRB is crucial not only for regional sustainability but also for informing broader climate regulation strategies and international policies aimed at mitigating climate change through nature-based solutions, highlighting the global significance of such regional deep-dives (Osland et al. 2017;Bellard et al. 2012). ...
Wetlands are vital for global carbon storage, yet face significant pressures. This study quantifies wetland landscape pattern changes and their impact on carbon storage in the transboundary Irtysh River Basin (IRB) from 2000 to 2020, identifies key landscape drivers, and projects future carbon storage under distinct scenarios for 2030. We utilized multi-temporal land cover data (GWL_FCS30), landscape metrics (Fragstats), the InVEST model for carbon storage estimation, interpretable machine learning (NGBoost coupled with SHAP analysis) to link landscape patterns to carbon dynamics, sensitivity analysis, and the PLUS model for scenario-based future projections (Natural Scenario - S1, Wetland Protection - S2, Wetland Degradation - S3). From 2000 to 2020, total wetland area increased by 10,417 km², primarily driven by marsh and swamp expansion, resulting in a net carbon storage increase from 2.827 × 10⁸ tC to 2.885 × 10⁸ tC (net gain: 5.8 × 10⁶ tC). Sensitivity analysis revealed high responsiveness (Sensitivity Index = 10.812) of carbon storage to wetland area change. The NGBoost model accurately predicted carbon storage based on landscape metrics (MSE = 0.682, RMSE = 0.8259, MAE = 0.7811). SHAP analysis identified the aggregation index (AI), largest patch index (LPI), and number of patches (NP) as the most critical landscape predictors influencing carbon storage. Future projections for 2030 estimate total carbon storage at 3.229 × 10⁸ tC under S1 (stabilization), increasing to 3.421 × 10⁸ tC under S2 (protection), but declining sharply to 1.871 × 10⁸ tC under S3 (degradation). Landscape structure, particularly aggregation and the extent of large patches, significantly influences wetland carbon storage in the IRB. Proactive wetland protection policies are crucial for enhancing and maintaining carbon sequestration capacity in this sensitive transboundary basin, contributing to regional climate change mitigation efforts.
Graphical abstract
This graphical abstract summarizes a study on wetland dynamics and carbon storage in the Irtysh River Basin (IRB) from 2000 to 2020, with 2030 projections, focusing on wetland conservation and carbon sink roles. Using GWL_FCS30 land use data, Fragstats 4.2, InVEST, NGBoost with SHAP, and the PLUS model, the study analyzes landscape patterns, estimates carbon storage, identifies key drivers (e.g., aggregation index, largest patch index), and simulates future scenarios. Results show marsh and swamp expansion, increased fragmentation, and carbon storage rising to 2.885 × 10⁸ tC by 2020. Projections for 2030 estimate 3.229 × 10⁸ tC (Natural Scenario), 3.421 × 10⁸ tC (Wetland Protection), and 1.871 × 10⁸ tC (Wetland Degradation). This visual highlights the importance of wetland conservation for enhancing carbon sequestration and informs sustainable land-use strategies in transboundary basins
... The thermal range for optimum physiological function is relatively narrow for most species, prompting many to expand their range poleward with climate-driven warming (Burrows et al., 2011;Pörtner & Farrell, 2008;Sorte et al., 2010). The movement of tropical species into higher latitudes results in the "tropicalization" of subtropical and temperate ecosystems (Bellard et al., 2012;Osland et al., 2021). Researchers have documented this phenomenon across diverse taxonomic groups and consider tropicalization a major driver of global species compositional change (Burrows et al., 2011;Hickling et al., 2006;Rosenzweig et al., 2007). ...
In response to warming temperatures, species worldwide are expanding their range poleward. As these species move into new ecosystems, they interact with novel organisms and may alter food webs. Climate-driven expansions can thus lead to cascading changes in ecological interaction webs, affecting ecosystem function and services. However, climate change rarely acts in isolation. Other anthropogenic stressors, such as pollution and habitat conversion, act in concurrence with the indirect, biotic effects of climate change. In this study, we employed gut content analysis to investigate dietary similarity between sheepshead (Archosargus probatocephalus) and an expanding tropical congener, sea bream (A. rhomboidalis), in the Indian River Lagoon, Florida (USA). We paired these data with long-term seagrass and macroalgae monitoring data to investigate the effects of a macrophyte cover gradient, as a proxy for eutrophication-driven die-offs, on the diets of these fish species. Sheepshead and sea bream had highly similar diets, dominated by macrophytes. Furthermore, tropical sea bream consumed more seagrass at locations with higher seagrass abundance compared to low seagrass abundance, whereas sheepshead consumed a similar amount across seagrass abundance levels. These results suggest sea bream have the potential to negatively affect future recoveries of currently declining sheepshead populations. Invasion of sea bream may also hinder recovery of imperiled seagrass populations by increasing grazing pressure in this eutrophic, light-limited system. We provide evidence that the indirect effects of climate change and other anthropogenic stressors can interact and influence ecological interactions.
... However, the effects of these changes are not uniform across the globe. Arid and semiarid regions are particularly vulnerable to climate change, and the plant species within these regions face significant challenges for survival under such stress conditions (Bellard et al., 2012;Diaz-Varela et al., 2010;Ernakovich et al., 2014;Feeley et al., 2011;Sproull et al., 2015). Machine learning models that can process large volumes of biological data and detect complex patterns within this data could be utilized for predicting the habitat suitability of plants (Chen and Jiang, 2021). ...
With the advancement in computer technologies, the prediction of ecological niches for various plant species has become possible. The impact of climate change on the distribution of plants could be investigated using species distribution models. This study aimed to identify the climatic and environmental factors influencing the distribution of Teucrium polium species and determine its geographic range in Kashmar and Khalilabad counties, Khorasan Razavi province, Iran. To achieve this, 75 bioclimatic variables encompassing soil, topography, climate, and geology factors were initially analyzed for correlation, and variables with correlation coefficients higher than 0.80 were eliminated. The data of 57 GPS-recorded presence points were collected from two areas during 2021 − 2022. The environmental data and presence points were processed and predicted using the BIOMOD2 package within the R software, which encompasses 11 models. The models were evaluated using Cohen's kappa coefficient (KAPPA), True Skill Statistic (TSS), and Receiver Operating Characteristic (ROC) indices. Model accuracy assessment revealed that the Random Forest (RF) model achieved 99.7% accuracy while the Ensemble model achieved 99.4% accuracy, indicating excellent modeling precision. The relative importance of different variables in the selected models were as follows: in the RF model, silt at a depth of 30 − 60 and 15 − 30 cm, topographic humidity index, annual mean temperature, and daily temperature range; and for Ensemble model, nitrogen at a depth of 15 − 30 cm, topographic humidity index, soil bulk density at a depth of 5 − 15 cm, silt at a depth of 30 − 60 cm, and nitrogen at a depth of 15 − 5 cm, highlighting the influence of soil factors on the species distribution. The obtained results could be utilized for the conservation, management, and expansion of Teucrium polium habitats in similar areas.
... As a result, these regions offer a favorable environment for U. kirkiana to survive and ought to be given priority in conservation planning for the species. Our findings align with previous research showing that species of tropical dry forests favor regions with lower seasonal temperature fluctuations, promoting a more expansive and stable range (Bellard et al., 2012). ...
... Notably, S. schinzianum is expected to undergo the most severe reductions in niche breadth. These findings align with broader ecological research indicating that climate change can lead to habitat loss and reduced distributional ranges for many plant species (Bellard et al. 2012;Urban 2015;Auffret and Svenning 2022;Weiskopf et al. 2024). ...
Plants with restricted distributions and small population sizes are particularly vulnerable to climate change. Sesamum species are ideal for species distribution modeling due to their ecological sensitivity, agricultural and economic importance, and wide geographic range, providing insights for conservation and policy. Global. Sesamum. We applied the maximum entropy (MaxEnt) model to assess the global ecological niche breadth of Sesamum species and examine how bioclimatic and soil variables influence their future (2080) distribution. We identified key environmental drivers and projected species‐specific range shifts under changing climatic conditions. MaxEnt models effectively predicted suitable habitats, with climate variables playing a dominant role. Precipitation of the wettest month (BIO13) was particularly influential for S. abbreviatum, S. alatum, and S. angustifolium, while temperature variables (BIO7, BIO11) were also key. Elevation moderately impacted S. angolense, while soil factors such as pH (S. abbreviatum) and clay content (S. angolense) exhibited species‐specific effects. Principal component analysis revealed variation in niche breadth, with S. indicum and S. schinzianum occupying broader ecological ranges, whereas S. saxicola and S. abbreviatum were more restricted. Future projections suggest 46.4% of the species will experience range contractions, with S. schinzianum facing the most significant decline. Conversely, 39.3% of the species, including S. imperatricis and S. abbreviatum, are expected to expand their ranges. Phylogenetic analyses indicate a random distribution of niche breadth and extinction risk across the genus. Our findings highlight the susceptibility of Sesamum species to climate change, emphasizing the need for urgent conservation actions. Prioritizing vulnerable species such as S. forbesii and S. sesamoides, alongside habitat restoration and long‐term monitoring, is crucial to mitigate population declines and prevent extinction.
... The exacerbation of climate-related stressors accelerated biodiversity loss, particularly among species with limited dispersal capabilities and specialized habitat requirements (Bellard et al., 2012). Habitat fragmentation, coupled with altered climatic conditions, led to a decline in population sizes and increased extinction rates (Urban, 2015). ...
... Climate change is frequently recognized as a significant threat to biodiversity, species survival, and the stability of ecosystems across various biomes (Maclean and Wilson 2011;Bellard et al. 2012). Extreme high temperatures and prolonged drought conditions, which result in various abiotic and biotic stresses, significantly impact the physiological mechanisms of plants as well as their growth, development, reproductive success, and distribution across different geographical areas (Kumar et al. 2021). ...
Woody plants offer valuable services to ecosystems, including providing useful products, stabilizing ecosystems, and mitigating climate and pollution effects. However, they face significant abiotic and biotic stresses, with climate change being the most critical challenge. It is essential to understand that reducing populations of woody species, particularly those found only in a specific area, can have severe and irreversible effects on the entire ecosystem. Therefore, exploring the potential influence of climate change on the distribution of endemic woody species is an appealing subject for conservation researchers. This study investigates how climate change affects the distribution of three endemic species of woody plants in the genus Colutea in Iran. The MaxEnt model was used to analyze the data, and the results showed that the model was effective for predicting the impact of climate change on the plants (AUC ≥ 0.9). The distribution of C. persica was significantly affected by solar radiation, Precipitation of Wettest Month, sand, and silt content. C. porphyrogamma's distribution was impacted by Mean Temperature of Coldest Quarter, Precipitation of Driest Month, and Cation Exchange Capacity, while C. triphylla was most affected by Precipitation Seasonality, Precipitation of Driest Quarter, and Isothermality. According to the findings, the distribution of these species is expected to decrease in the 2050s and 2070s due to climate change, based on the RCP4.5 and RCP8.5 climate scenarios. These findings can be useful for developing strategies to manage the impacts of climate change on these species.
... 《昆明-蒙特利尔全球生物 多样性框架》也提出了以多种方式应对气候变化对生 物多样性影响的生物多样性保护目标(目标8) [5] . [28] . 尽管物种分布模 型因其较高的不确定性受到质疑 [29,30] , 但通过对物 种分布与环境因子关系的理论研究、对模型构建方 法的探索以及对不同种类的模型集成分析等, 生态学 者针对造成SDMs不确定性的各个因素进行了深入 研究以降低SDMs的不确定性, 逐步提升了SDMs的 可用性 [31] . ...
Coğrafya Haritaları ve CBS Üzerine Akademik Bir İnceleme Şule DEMİR Coğrafi Bilgi Sistemleri ve Jeomorfoloji Haritaları Onur YAYLA Coğrafi Bilgi Sistemleri ile Biyocoğrafya, İklim ve Toprak Araştırmaları Seda AKKURT GÜMÜŞ Doğal Afet Yönetiminde Web CBS Kullanımı: Samsun Üniversitesi Afet/Acil Durum Bilgi ve Destek Sistemi (SADES) Fatih OCAK Ege Bölgesinde Yaz Mevsiminde (2024 Yılı) Yanan Alanların Gee (Google Earth Engine) ve CBS Kullanılarak Belirlenmesi ve Yanan Alanların Hesaplanması Aykut CAMCI Arazi Kullanımı ve Arazi Örtüsü Değişiminin Kontrollü Sınıflandırma Yöntemi ile Analizi: Çiçekdağı Kütlesinin Doğu Kesimi (Kırşehir/Türkiye) Emre ALTUNTAŞ Halithan ŞEN Muhammet BAHADIR Coğrafi Bilgi Sistemleri ve Nüfus Mustafa KÖSE CBS ve Harita Tasarımı Emre DUMAN Coğrafi Bilgi Sistemlerinde İlişkisel Veritabanı Yönetimi ve Tasarımı Ahmet ŞAHAP Coğrafi Bilgi Sistemlerinde Mekânsal Analiz ve Modelleme Yaklaşımları Çağan ALEVKAYALI
Luprops orientalis (Motschulsky, 1868) is an economically important pest in traditional Chinese medicines, widely distributed in East Asia. However, the primary limiting factors affecting its distribution, potential suitable areas, as well as its response to global warming, remain largely unknown. Utilizing 295 filtered distribution points and 10 environmental variables (9 climate variables and 1 land cover type), this study uses the MaxEnt model to predict the potential distribution of L. orientalis under near-current and future environmental change scenarios. The results indicated that precipitation of the warmest quarter (bio18), temperature seasonality (bio04), and precipitation of the wettest month (bio13) were the most significant environmental variables affecting the distribution of suitable habitats for L. orientalis, while the contribution of average variation in daytime temperature (bio2) was the smallest. Under the near-current climate, the areas of low, moderate, and high suitability for L. orientalis are approximately 1.02 × 106 km2, 1.65 × 106 km2, and 8.22 × 105 km2, respectively. The suitable areas are primarily located in North China, Central China, the Korean Peninsula, and Central and Southern Japan. Under future climate conditions, the potential suitable areas are expected to expand significantly, especially in Central China. However, the high-suitability areas in North China are predicted to experience a slight reduction. With the increase in carbon emission concentrations, the suitable area shows an increasing trend in the 2050s, followed by a declining trend in the 2090s. The centroids of suitable areas will shift to the northeast in the future. These findings enhance our understanding of how climate change affects the distribution of L. orientalis and will assist governments in formulating effective pest control strategies, including widespread monitoring and stringent quarantine measures.
Abiotic stress refers to the negative effects on plant growth and development caused by abiotic factors such as extreme temperatures, drought, salinity, floods and pollutants. On the other hand, biotic stress is caused by living organisms such as pathogens (disease-causing microorganisms) and pests (insects, mites, and rodents) that can harm plants. The interaction between abiotic stress and biotic stress can have a significant impact on plant health and productivity. Drought stress weakens plants, making them more susceptible to pathogen attack. Lack of water can hinder a plant's defense response, making it harder for it to fight disease. Pathogens can quickly colonize and spread in drought-stressed trees, causing more serious damage. Increased soil salinity can interfere with normal physiological processes in plants, leading to reduced growth and yield.
One Health's interdisciplinary approach has been effective at the nexus of human and animal health but often overlooks environmental health, including wildland fire. Fire management seeks to suppress dangerous fires and to manage others for resource benefit, which inherently pits human health against the health of fire-dependent biodiversity. One Health may better address past failures to achieve fire management goals by providing a more comprehensive and cohesive framework explicitly recognizing interconnectedness of plant, animal, human, and environmental health. Although there are exceptions, we suggest novel health solutions and maximal health benefits will most often result from pyrohealth synchrony: actively aligning contemporary fire management with historic fire-regimes (i.e., long-term patterns in fire frequency, intensity, severity, seasonality, and spatial extent). We also present a process for making fire-integrated One Health an applied reality capable of galvanizing stakeholders around interventions that better interconnect fire to the health of plants, animals, people, and environments.
Carbon and nitrogen are central elements in global biogeochemical cycles. To effectively manage carbon and nitrogen in China, we developed a comprehensive model for quantifying their fluxes, investigating their interplay across 16 human and natural subsystems. Between 1980 and 2020, nitrogen losses in China increased 2.3-fold and carbon emissions surged 6.5-fold. Integrated carbon and nitrogen management holds the potential for a 74% reduction in nitrogen losses to air and water and a 91% decrease in carbon emissions to the atmosphere by 2060. Compared with separate control of carbon or nitrogen, integrated management delivers an additional reduction of 1.8 million tons of nitrogen and 26.5 million tons of carbon by 2060, bringing out a 37% decrease in unit abatement cost and a net societal benefit of 1384 billion USD.
At the edge of an ongoing expansion, pioneer individuals encounter novel ecological and evolutionary pressures that may not be experienced by conspecifics settled in long-colonised areas. Consistent behavioural differences among conspecifics (animal personality) may be important determinants of individuals’ successful colonisation of novel environments and range expansion. By enhancing an individual's ability to find food and shelter as well as increasing its capacity to navigate novel environments, behavioural traits such as exploration and risk-taking are thus expected to be more highly expressed in populations undergoing expansion than in established populations.
We investigated among-individual variation in behaviours associated to risk-taking and exploratory tendencies in populations of small mammals during different stages of the colonisation process. Using a standardized behavioural test in the field, we quantified exploration and boldness of striped field mice (Apodemus agrarius, N=95) from six subpopulations from Germany, where they are established, and in Slovakia, where a recolonisation of the area is currently in progress, and in control species bank voles (Myodes glareolus, N=76) that shared the same habitats but were long-established at all sites.
Striped field mice in the expanding populations were significantly slower in exploring the open field arena, while showing comparable levels of risk taking compared to conspecifics from established populations. No difference in behaviour was detected between the populations of bank voles. Our results suggest that a slow exploration strategy might play an advantageous role in expansion processes of small mammal populations.
Understanding the potential distribution patterns and habitat suitability of threatened species under climate change scenarios is essential for conservation efforts. This study aimed to assess the current and future distribution patterns of the endangered Cycas taiwaniana in China using the MaxEnt model under two contrasting climate change scenarios: SSP1-2.6 (low emissions) and SSP3-7.0 (high emissions), projected for the 2050s and 2070s periods. The model identified key bioclimatic variables influencing habitat suitability, including Annual Mean Temperature, Mean Diurnal Range, and Temperature Seasonality. Under current climate conditions, the species’ most suitable habitats are primarily located in southern coastal regions, with Hainan Island showing exceptional suitability. However, future projections under the moderate emission (SSP1-2.6) scenario suggest a significant shrinking of suitable habitat areas, particularly a 27.5% decline in excellent and a 35% decrease in good categories by the 2070s. In contrast, under the high-emission scenario (SSP3-7.0), while an initial decline in suitable habitats is projected, the model predicts an unexpected expansion of highly suitable areas by 2070, particularly in Guangxi, Guangdong, and Fujian coastal regions. The results highlight the vulnerability of C. taiwaniana to climate change and underscore the importance of developing adaptive conservation strategies to mitigate potential habitat loss. The findings also emphasize the need for further research on species-specific responses to climate change and the development of proactive measures to safeguard the future distribution of this threatened species.
Climate change has greatly affected the survival and distribution of various species. Understanding the distribution of species and their responses to climate change is helpful for species conservation and the utilization of germplasm resources. Carpinus fangiana is endemic to China, and it is used as an ornamental plant and in traditional Chinese medicine. However, its distribution remains unclear. In this study, we aimed to reconstruct the current and future ecological niches of C. fangiana. The prediction results indicated that annual precipitation and elevation are the key factors limiting its distribution. Our research found that it also exists in southern Chongqing and southwestern Hunan, and distinct suitable distribution areas and core suitable areas have been detected in these areas. Currently, the suitable distribution areas and core suitable areas of C. fangiana are mainly located in southwestern China around the Sichuan Basin. Although it is distributed in southeastern Yunnan, no distinct suitable distribution areas were detected there. In contrast, suitable distribution areas and core suitable areas were detected in the Qinling and Dabashan mountains, the mountainous areas in western Hubei, and southeastern Xizang, where C. fangiana is not currently distributed. Future climate change will likely have a considerable impact on its distribution, with a clear trend of suitable distribution areas migrating toward higher latitudes and elevations. The suitable distribution areas located in southeastern Xizang and northwestern Yunnan are expected to be lost in the future. In particular, under the high-concentration scenario, a substantial loss of suitable distribution areas is predicted.
The transition from fossil-energy systems to renewable energy is a necessary step in addressing the issue of climate change. However, the solution to climate change cannot be achieved in isolation from the surrounding natural environment and societies. Chap. 2 provides a more detailed examination of three planetary boundaries that are strongly interlinked and that also relate closely to renewable energy production: climate change, biosphere integrity (biodiversity loss), and land system change. The chapter provides a general overview of the concept of the carbon budget and the Earth’s annual biocapacity, emphasizing the importance of biodiversity to humanity and the impacts of land use resulting from energy production. The chapter also presents a case example of how to measure the biodiversity footprint of a large-scale energy project. Furthermore, the principles of social sustainability and the measures of a good life are introduced, with particular emphasis on the importance of considering the social aspects of large-scale energy projects. The chapter also highlights the importance and means of social participation and how power relations influence energy policy decision making. Finally, basic economic tools to evaluate the economic feasibility of renewable energy projects are presented. Energy engineers should have a solid foundational understanding of these different aspects of energy projects in their everyday work in designing and building sustainable energy systems for a de-carbonized, sustainable, and just future.
Camptotheca acuminata Decne. is an endemic and valuable tree species in China that is renowned for its medicinal and economic value due to secondary metabolites like camptothecin, a potent anti-cancer compound. With wild resources dwindling, it is a key protected species. Predicting and analyzing its suitable habitats under different future environmental scenarios is essential for conservation, introduction, development, and planting strategies. This study used 1008 distribution points and 32 environmental factors, applying the MaxEnt v3.4.4 model and ArcGIS v10.7 software to predict C. acuminata’s potential distribution under four greenhouse gas emission scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) for the present, 2050, and 2070. This study identifies the key environmental factors influencing its distribution and analyzes habitat trends under various ecological scenarios. The dominant environmental factors are Bio6 (contribution 23%; importance 59.8%), human activity factor (contribution 18.6%; importance 15.7%), Slope2 (contribution 1%; importance 7%), Slope3 (contribution 5.1%; importance 3.4%), elevation (contribution 0.9%; importance 1.7%), and Bio14 (contribution 41.2%; importance 1%). The total potential suitable habitat area for C. acuminata is 1.5796 × 10⁴ km². Except under RCP8.5, where the habitat area continuously increases, the habitat area shows a trend of first increasing and then decreasing. When human activity is considered, the total potential suitable habitat area is 1.8495 × 10⁴ km², with a consistent decrease under all scenarios except RCP8.5. Centroid migration analysis shows that, driven by global warming, the suitable habitats for C. acuminata are shifting toward higher latitudes. This study provides theoretical support for the conservation, resource management, and germplasm protection of C. acuminata under future ecological and environmental changes.
Climate change presents significant challenges to plant growth and reproduction. Clonal plants, with low genetic diversity, are particularly vulnerable due to their limited adaptive capacity. Plant-associated microbiomes can play a crucial role in enhancing clonal plant survival and adaptability, yet the mechanisms governing microbial community assembly along the soil-episphere-endosphere continuum remain unclear. In this study, we investigated microbial community assembly patterns in the clonal plant Glechoma longituba . Our findings demonstrate that the assembly of microbial communities is primarily driven by host-related factors rather than external environmental filtering. First, host selection reduced α-diversity and network complexity while increasing β-diversity and community stability. Second, the mechanisms of microbial assembly transitioned from stochastic dominance in bulk soil and epiphytic compartments to deterministic processes within endophytic niches. Third, the taxonomic structure exhibited significant turnover along the soil-episphere-endosphere continuum, accompanied by functional redundancy to maintain ecosystem functions. The results support the hypothesis that host selection optimizes the functional composition of microbial communities by reducing diversity and network complexity while ensuring the stability of key functional microorganisms. The study emphasizes the critical role of host-microbe interactions in sustaining the adaptive and functional advantages of clonal plants, offering insights into managing sustainable plant communities under climate change.
IMPORTANCE
This study highlights the vital role of plant-associated microbiomes in helping clonal plants, which have low genetic diversity, adapt to climate change. By examining the clonal plant Glechoma longituba , the research reveals that the plant itself plays a key role in shaping its microbial communities, rather than external environmental factors. Host selection simplifies microbial diversity and network complexity but enhances community stability and functional efficiency. These findings suggest that clonal plants can optimize their microbiomes to maintain critical functions. This work provides valuable insights into how plants and microbes interact to improve resilience, offering potential strategies for managing plant communities in a changing climate. By understanding these mechanisms, we can better support sustainable ecosystems and agricultural practices in the face of global environmental challenges.
Rising temperatures may negatively impact rural landscapes in temperate climates due to reduced yields in agriculture and forestry, an increased risk of biodiversity loss, changes in the local climate and a decrease in recreational value. One promising way to mitigate increasing land surface temperatures (LST) in rural landscapes is to implement land-use and land-cover changes as adaptation measures that retain precipitation in soils, water bodies, and groundwater to allow vegetation to evaporate more water to reduce LST in summer. We develop an integrated modelling procedure to identify cost-effective spatially differentiated adaptation measures in agriculture and forestry to mitigate LST increases. We define cost-effective adaptation in a landscape as maximizing LST mitigation for given costs. The procedure combines the results of a model that predicts the spatially differentiated effects of adaptation measures on LST with the results of an economic model that estimates the respective spatially differentiated costs in an optimisation algorithm. We demonstrate how the procedure works by applying it to the Elbe-Elster-county in Germany. We find that a substantial share of results can only be explained by considering spatially differentiated costs and mitigation impacts and not average values showing the importance of taking into account costs and impacts of measures in a spatially differentiated manner. We also compare results from our integrated modelling procedure with a (purely natural science) approach that selects those adaptation measures first which perform best in terms of LST mitigation and find that our approach leads to a better heat mitigation effect by a factor of 3.5 – 4.8.
The presence of Miomantis paykullii has been identified for the first time in Türkiye, Cyprus, and Spain, while Ameles spallanzania has been identified for the first time in Slovakia, Romania, Luxembourg, and Türkiye. Records from social media and citizen science platforms suggest that the spread of these species may be influenced by human activities, particularly transportation and landscaping, similar to previously proposed hypotheses, as all observations were made in anthropogenic areas. Considering previous reports and new records related to these two species, researchers should pay attention to their ability to adapt easily to new regions and their potential to become invasive.
A new computation framework (BIOMOD: BIOdiversity MODelling) is presented, which aims to maximize the predictive accuracy of current species distributions and the reliability of future potential distributions using different types of statistical modelling methods. BIOMOD capitalizes on the different techniques used in static modelling to provide spatial predictions. It computes, for each species and in the same package, the four most widely used modelling techniques in species predictions, namely Generalized Linear Models (GLM), Generalized Additive Models (GAM), Classification and Regression Tree analysis (CART) and Artificial Neural Networks (ANN). BIOMOD was applied to 61 species of trees in Europe using climatic quantities as explanatory variables of current distributions. On average, all the different modelling methods yielded very good agreement between observed and predicted distributions. However, the relative performance of different techniques was idiosyncratic across species, suggesting that the most accurate model varies between species. The results of this evaluation also highlight that slight differences between current predictions from different modelling techniques are exacerbated in future projections. Therefore, it is difficult to assess the reliability of alternative projections without validation techniques or expert opinion. It is concluded that rather than using a single modelling technique to predict the distribution of several species, it would be more reliable to use a framework assessing different models for each species and selecting the most accurate one using both evaluation methods and expert knowledge.
Projected climate warming will potentially have profound effects on the earth's biota, including a large redistribution of tree species. We developed models to evaluate potential shifts for 80 individual tree species in the eastern United States. First, environmental factors associated with current ranges of tree species were assessed using geographic information systems (GIS) in conjunction with regression tree analysis (RTA). The method was then extended to better understand the potential of species to survive and/ or migrate under a changed climate. We collected, summarized, and analyzed data for climate, soils, land use, elevation, and species assemblages for .2100 counties east of the 100th meridian. Forest Inventory Analysis (FIA) data for .100 000 forested plots in the East provided the tree species range and abundance information for the trees. RTA was used to devise prediction rules from current species-environment relationships, which were then used to replicate the current distribution as well as predict the future potential distri- butions under two scenarios of climate change with twofold increases in the level of at- mospheric CO2. Validation measures prove the utility of the RTA modeling approach for mapping current tree importance values across large areas, leading to increased confidence in the predictions of potential future species distributions. With our analysis of potential effects, we show that roughly 30 species could expand their range and/or weighted importance at least 10%, while an additional 30 species could decrease by at least 10%, following equilibrium after a changed climate. Depending on the global change scenario used, 4-9 species would potentially move out of the United States to the north. Nearly half of the species assessed (36 out of 80) showed the potential for the ecological optima to shift at least 100 km to the north, including seven that could move .250 km. Given these potential future distributions, actual species redistributions will be controlled by migration rates possible through fragmented landscapes.
Range shifts due to climate change may cause species to move out of protected areas. Climate change could therefore result in species range dynamics that reduce the relevance of current fixed protected areas in future conservation strategies. Here, we apply species distribution modeling and conservation planning tools in three regions (Mexico, the Cape Floristic Region of South Africa, and Western Europe) to examine the need for additional protected areas in light of anticipated species range shifts caused by climate change. We set species representation targets and assessed the area required to meet those targets in the present and in the future, under a moderate climate change scenario. Our findings indicate that protected areas can be an important conservation strategy in such a scenario, and that early action may be both more effective and less costly than inaction or delayed action. According to our projections, costs may vary among regions and none of the three areas studied will fully meet all conservation targets, even under a moderate climate change scenario. This suggests that limiting climate change is an essential complement to adding protected areas for conservation of biodiversity.
a b s t r a c t Global climate change poses an immense challenge for conservation biologists seeking to mitigate impacts to species and ecosystems. Species persistence will depend on geographic range shifts or adap-tation in response to warming patterns as novel climates and community assemblages arise. Assisted col-onization has been proposed as a method for addressing these challenges. This technique, which consists of transporting species to a new range that is predicted to be favorable for persistence under future climate scenarios, has become the subject of controversy and discussion in the conservation community due to its highly manipulative nature, questions about widespread feasibility, and uncertainty associated with the likelihood of translocated species becoming invasive. We reviewed the discussion and criticism associated with assisted colonization and sought to identify other conservation techniques that also dis-play potential to promote the colonization and adaptation of species in response to climate change. We propose an integrated conservation strategy that includes management for habitat connectivity, conser-vation genetics, and when necessary, assisted colonization of species that are still unable to shift their ranges even given implementation of the above standard conservation approaches. We argue that this integrated approach will facilitate persistence for a larger proportion of species than is possible by solely using assisted colonization. Furthermore, a multi-faceted approach will likely reduce the uncertainty of conservation outcomes and will become increasingly necessary for conservation of biodiversity in a changing climate.
Abstract The GLOBIO3 model has been developed to assess human-induced changes in biodiversity, in the past, present, and future at regional and global scales. The model is built on simple cause–effect relationships between environmental drivers and biodiversity impacts, based on state-of-the-art knowledge. The mean abundance of original species relative to their abundance in undisturbed ecosystems (MSA) is used as the indicator for biodiversity. Changes in drivers are derived from the IMAGE 2.4 model. Drivers considered are land-cover change, land-use intensity, fragmentation, climate change, atmospheric nitrogen deposition, and infrastructure development. GLOBIO3 addresses (i) the impacts of environmental drivers on MSA and their relative importance; (ii) expected trends under various future scenarios; and (iii) the likely effects of various policy response options. GLOBIO3 has been used successfully in several integrated regional and global assessments. Three different global-scale policy options have been evaluated on their potential to reduce MSA loss. These options are: climate-change mitigation through expanded use of bio-energy, an increase in plantation forestry, and an increase in protected areas. We conclude that MSA loss is likely to continue during the coming decades. Plantation forestry may help to reduce the rate of loss, whereas climate-change mitigation through the extensive use of bioenergy crops will, in fact, increase this rate of loss. The protection of 20% of all large ecosystems leads to a small reduction in the rate of loss, provided that protection is effective and that currently degraded protected areas are restored.
Mountain ecosystems will likely be affected by global warming during the 21st century, with substantial biodiversity loss predicted by species distribution models (SDMs). Depending on the geographic extent, elevation range, and spatial resolution of data used in making these models, different rates of habitat loss have been predicted, with associated risk of species extinction. Few coordinated across-scale comparisons have been made using data of different resolutions and geographic extents. Here, we assess whether climate change-induced habitat losses predicted at the European scale (10 × 10′ grid cells) are also predicted from local-scale data and modeling (25 m × 25 m grid cells) in two regions of the Swiss Alps. We show that local-scale models predict persistence of suitable habitats in up to 100% of species that were predicted by a European-scale model to lose all their suitable habitats in the area. Proportion of habitat loss depends on climate change scenario and study area. We find good agreement between the mismatch in predictions between scales and the fine-grain elevation range within 10 × 10′ cells. The greatest prediction discrepancy for alpine species occurs in the area with the largest nival zone. Our results suggest elevation range as the main driver for the observed prediction discrepancies. Local-scale projections may better reflect the possibility for species to track their climatic requirement toward higher elevations.
Today's scientists are facing the enormous challenge of predicting how cli-mate change will affect species distributions and species assemblages. To do so, ecologists are widely using phenomenological models of species dis-tributions that mainly rely on the concept of species niche and generally ignore species' demography, species' adaptive potential, and biotic interac-tions. This review examines the potential role of the emerging synthetic disci-pline of evolutionary community ecology in improving our understanding of how climate change will alter future distribution of biodiversity. We review theoretical and empirical advances about the role of niche evolution, inter-specific interactions, and their interplay in altering species geographic ranges and community assembly. We discuss potential ways to integrate complex feedbacks between ecology and evolution in ecological forecasting. We also point at a number of caveats in our understanding of the eco-evolutionary consequences of climate change and highlight several challenges for future research.
1] A number of previous modeling studies have assessed the implications of projected CO 2 -induced climate change for future terrestrial ecosystems. However, although current understanding of possible long-term response of vegetation to elevated CO 2 and CO 2 -induced climate change in some geographical areas (e.g., the high-latitude regions) has been strengthened by dint of accumulating evidence from these past studies, it is still weak in others. This study examines the responses of global potential natural vegetation distribution, net primary production (NPP), and fire emissions to future changes in atmospheric CO 2 concentration and climate using the National Center for Atmospheric Research Community Land Model's dynamic global vegetation model. The model is run to vegetative equilibrium (i.e., with respect to leaf area index (LAI) and vegetation coverage) driven with preindustrial climate and future climate near 2100, respectively, simulated by eight general circulation models (GCMs). The simulated potential vegetation under the preindustrial control mean climate (CO 2 concentration held at 275 ppm) is compared with that under the SRESA1B 2100 mean climate (CO 2 concentration stabilizes at 720 ppm beyond 2100). Simulated vegetation response ranges from mild changes of the fractional coverage of different plant functional types to the rather dramatic changes of dominant plant functional types. Although such response differs significantly across different GCM climate projections, a quite consistent spatial pattern emerges, characterized by a considerable poleward spread or shift of temperate and boreal forests in the Northern Hemisphere high latitudes, and a substantial degradation of vegetation type in the tropics (e.g., increase of drought deciduous trees coverage at the expense of evergreen trees) especially in portions of West and southern Africa and South America. Despite the widespread degradation of vegetation type in the tropics, NPP, and growing season LAI are predicted to increase under most GCM scenarios over most of the globe. Carbon fluxes to the atmosphere due to fire generally increase too across the globe. Such responses of NPP and fire occurrence result from the synergistic effects of CO 2 concentration changes, climate changes, and vegetation changes. In the HadCM-driven simulation, however, extreme responses are shown in some regions: Deciduous forest is replaced by grasses in large areas in the middle latitudes, and substantial areas in northern South America and southern Africa predominantly covered by evergreen forest are replaced with grasses while NPP and fire emissions reduce drastically (by more than 100%). A future paper will examine how the biosphere response documented here influences the impact of climate change on surface hydrological conditions. Citation: Alo, C. A., and G. Wang (2008), Potential future changes of the terrestrial ecosystem based on climate projections by eight general circulation models, J. Geophys. Res., 113, G01004, doi:10.1029/2007JG000528.
Bioclimatic models are the primary tools for simulating the impact of climate change on species distributions. Part of the uncertainty in the output of these models results from uncertainty in projections of future climates. To account for this, studies often simulate species responses to climates predicted by more than one climate model and/or emission scenario. One area of uncertainty, however, has remained unexplored: internal climate model variability. By running a single climate model multiple times, but each time perturbing the initial state of the model slightly, different but equally valid realizations of climate will be produced. In this paper, we identify how ongoing improvements in climate models can be used to provide guidance for impacts studies. In doing so we provide the first assessment of the extent to which this internal climate model variability generates uncertainty in projections of future species distributions, compared with variability between climate models. We obtained data on 13 realizations from three climate models (three from CSIRO Mark2 v3.0, four from GISS AOM, and six from MIROC v3.2) for two time periods: current (1985–1995) and future (2025–2035). Initially, we compared the simulated values for each climate variable (P, Tmax, Tmin, and Tmean) for the current period to observed climate data. This showed that climates simulated by realizations from the same climate model were more similar to each other than to realizations from other models. However, when projected into the future, these realizations followed different trajectories and the values of climate variables differed considerably within and among climate models. These had pronounced effects on the projected distributions of nine Australian butterfly species when modelled using the BIOCLIM component of DIVA-GIS. Our results show that internal climate model variability can lead to substantial differences in the extent to which the future distributions of species are projected to change. These can be greater than differences resulting from between-climate model variability. Further, different conclusions regarding the vulnerability of species to climate change can be reached due to internal model variability. Clearly, several climate models, each represented by multiple realizations, are required if we are to adequately capture the range of uncertainty associated with projecting species distributions in the future.
1. Spatially explicit understanding of the delivery of multiple ecosystem services (ES) from global to local scales is currently limited. New studies analysing the simultaneous provision of multiple services at landscape scale should aid the understanding of multiple ES delivery and trade-offs to support policy, management and land planning.
2. Here, we propose a new approach for the analysis, mapping and understanding of multiple ES delivery in landscapes. Spatially explicit single ES models based on plant traits and abiotic characteristics are combined to identify ‘hot’ and ‘cold’ spots of multiple ES delivery, and the land use and biotic determinants of such distributions. We demonstrate the value of this trait-based approach as compared to a pure land-use approach for a pastoral landscape from the central French Alps, and highlight how it improves understanding of ecological constraints to, and opportunities for, the delivery of multiple services.
3. Vegetative height and leaf traits such as leaf dry matter content were response traits strongly influenced by land use and abiotic environment, with follow-on effects on several ecosystem properties, and could therefore be used as functional markers of ES.
4. Patterns of association among ES were related to the dominant traits underlying different ecosystem properties. The functional decoupling between height and leaf traits provided alternative pathways for high agronomic value, as well as determining hot and cold spots of ES. Traditional land uses such as organic fertilization and mowing or altitude summer grazing were also linked with ES hot spots, because functional characteristics supporting fodder production and quality are compatible with species and functional diversity.
5. Synthesis. Analyses of ES using plant functional variation across landscapes are a powerful approach to understanding the fundamental ecological mechanisms underlying ES provision, and trade-offs or synergies among services. Sustainable management of species and functionally diverse grassland could simultaneously aim at conserving biodiversity and locally important ES by taking advantage of correlations and trade-offs among different plant functional traits.
Good forecasts of climate change impacts on extinction risks are critical for effective conservation management responses. Species distribution models (SDMs) are central to extinction risk analyses. The reliability of predictions of SDMs has been questioned because models often lack a mechanistic underpinning and rely on assumptions that are untenable under climate change. We show how integrating predictions from fundamentally different modeling strategies produces robust forecasts of climate change impacts on habitat and population parameters. We illustrate the principle by applying mechanistic (Niche Mapper) and correlative (Maxent, Bioclim) SDMs to predict current and future distributions and fertility of an Australian gliding possum. The two approaches make congruent, accurate predictions of current distribution and similar, dire predictions about the impact of a warming scenario, supporting previous correlative-only predictions for similar species. We argue that convergent lines of independent evidence provide a robust basis for predicting and managing extinctions risks under climate change.
Rapid anthropogenic climate change is already affecting species distributions and ecosystem functioning worldwide. We applied niche-based models to analyse the impact of climate change on tree species and functional diversity in Europe. Present-day climate was used to predict the distributions of 122 tree species from different functional types (FT). We then explored projections of future distributions under one climate scenario for 2080, considering two alternative dispersal assumptions: no dispersal and unlimited dispersal. The species-rich broadleaved deciduous group appeared to play a key role in the future of different European regions. Temperate areas were projected to lose both species richness and functional diversity due to the loss of broadleaved deciduous trees. These were projected to migrate to boreal forests, thereby increasing their species richness and functional diversity. Atlantic areas provided an intermediate case, with a predicted reduction in the numbers of species and occasional predicted gains in functional diversity. This resulted from a loss in species within the broadleaved deciduous FT, but overall maintenance of the group. Our results illustrate the fact that both species-specific predictions and functional patterns should be examined separately in order to assess the impacts of climate change on biodiversity and gain insights into future ecosystem functioning.
Climate change affects all levels of biology and is a major threat for biodiversity. Hence, it is fundamental to run biodiversity
monitoring programs to understand the effects of climate change on the biota and to be able to adjust management and conservation
accordingly. So far, however, very few existing monitoring programs allow for the detection of climate change effects, as
shown by a survey undertaken by the European project EuMon. Despite this shortcoming, several methods exist which allow to
make inferences from existing data by integrating data across different monitoring programs: correlative analyses, meta-analyses
and models. In addition, experiments are thought to be useful tools to understand the effects of climate change on plants
and animals. Here, we evaluate the utility of these four main approaches. All these methods allow to evaluate long term effects
of climate change and make predictions of species’ future development, but they are arguable. We list and compare their benefits
and inconveniences, which can lead to uncertainties in the extrapolation of species responses to global climate change. Individual
characteristics and population parameters have to be more frequently monitored. The potential evolution of a species should
be also modelled, to extrapolate results across spatial and temporal scales as well as to analyse the combined effects of
different climatic and biotic factors, including intra but also interspecific relationships. We conclude that a combination
of methodologies would be the most promising tool for the assessment of biological responses to climate change, and we provide
some thoughts about how to do so. Particularly, we encourage long-term studies along natural gradients (altitudinal or latitudinal)
on the same species/habitats to be able to extrapolate to large geographic scales, and to have more complete data sets, necessary
to understand the mechanisms of responses. Such data may provide a more accurate base for simulations across spatial and temporal
scales, especially if they are publicly available in a common database. These recommendations could allow the adaptation of
species management and the development of conservation tools to climate change which threatens species.
In the current review we wish to draw attention to an additional aspect of invasive species and climate change, that of agricultural
productivity and food security. We recognize that at present, such a review remains, in part, speculative, and more illustrative
than definitive. However, recent events on the global stage, particularly in regard to the number of food riots that occurred
during 2008, even at a time of record harvests, have prompted additional interest in those factors, including invasive species,
which could, through climatic uncertainty, alter food production. To that end, as agricultural scientists, we wish to begin
an initial evaluation of key questions related to food production and climate change including: how vulnerable is agriculture
to invasive species?; are current pest management strategies sufficient to control invasive outbreaks in the future?; what
are the knowledge gaps?; can we provide initial recommendations for scientists, land managers and policy makers in regard
to available resources? Our overall goals are to begin a synthesis of potential impacts on productivity, to identify seminal
research areas that can be addressed in future research, and to provide the scientific basis to allow agronomists and land
managers to formulate mitigation and adaptation options regarding invasive species and climate change as a means to maintain
food security.
The demand for accurate forecasting of the effects of global warming on biodiversity is growing, but current methods for forecasting
have limitations. In this article, we compare and discuss the different uses of four forecasting methods: (1) models that
consider species individually, (2) niche-theory models that group species by habitat (more specifically, by environmental
conditions under which a species can persist or does persist), (3) general circulation models and coupled ocean–atmosphere–biosphere
models, and (4) species–area curve models that consider all species or large aggregates of species. After outlining the different
uses and limitations of these methods, we make eight primary suggestions for improving forecasts. We find that greater use
of the fossil record and of modern genetic studies would improve forecasting methods. We note a Quaternary conundrum: While
current empirical and theoretical ecological results suggest that many species could be at risk from global warming, during
the recent ice ages surprisingly few species became extinct. The potential resolution of this conundrum gives insights into
the requirements for more accurate and reliable forecasting. Our eight suggestions also point to constructive synergies in
the solution to the different problems.
Quantitative scenarios are coming of age as a tool for evaluating the impact of future socioeconomic development pathways on biodiversity and ecosystem services. We analyze global terrestrial, freshwater, and marine biodiversity scenarios using a range of measures including extinctions, changes in species abundance, habitat loss, and distribution shifts, as well as comparing model projections to observations. Scenarios consistently indicate that biodiversity will continue to decline over the 21st century. However, the range of projected changes is much broader than most studies suggest, partly because there are major opportunities to intervene through better policies, but also because of large uncertainties in projections.
Local extinction of species can occur with a substantial delay following habitat loss or degradation. Accumulating evidence suggests that such extinction debts pose a significant but often unrecognized challenge for biodiversityconservation across a wide range of taxa and ecosystems. Species with long generation times and populations near their extinction threshold are most likely to have an extinction debt. However, as long as a species that is predicted to become extinct still persists, there is time for conservation measures such as habitat restoration and landscape management. Standardized long-term monitoring, more high-quality empirical studies on different taxa and ecosystems and further development of analytical methods will help to better quantify extinction debt and protect biodiversity.
There is ample evidence for ecological responses to recent climate change. Most studies to date have concentrated on the effects of climate change on individuals and species, with particular emphasis on the effects on phenology and physiology of organisms as well as changes in the distribution and range shifts of species. However, responses by individual species to climate change are not isolated; they are connected through interactions with others at the same or adjacent trophic levels. Also from this more complex perspective, recent case studies have emphasized evidence on the effects of climate change on biotic interactions and ecosystem services. This review highlights the 'knowns' but also 'unknowns' resulting from recent climate impact studies and reveals limitations of (linear) extrapolations from recent climate-induced responses of species to expected trends and magnitudes of future climate change. Hence, there is need not only to continue to focus on the impacts of climate change on the actors in ecological networks but also and more intensively to focus on the linkages between them, and to acknowledge that biotic interactions and feedback processes lead to highly complex, nonlinear and sometimes abrupt responses.
Rapid climate change has been implicated as a cause of evolution in poorly adapted populations. However, phenotypic plasticity
provides the potential for organisms to respond rapidly and effectively to environmental change. Using a 47-year population
study of the great tit (Parus major) in the United Kingdom, we show that individual adjustment of behavior in response to the environment has enabled the population
to track a rapidly changing environment very closely. Individuals were markedly invariant in their response to environmental
variation, suggesting that the current response may be fixed in this population. Phenotypic plasticity can thus play a central
role in tracking environmental change; understanding the limits of plasticity is an important goal for future research.
This article was submitted without an abstract, please refer to the full-text PDF file.
Projected climate warming will potentially have profound effects on the earth's biota, including a large redistribution of tree species. We developed models to evaluate potential shifts for 80 individual tree species in the eastern United States. First, environmental factors associated with current ranges of tree species were assessed using geographic information systems (GIS) in conjunction with regression tree analysis (RTA). The method was then extended to better understand the potential of species to survive and/or migrate under a changed climate. We collected, summarized, and analyzed data for climate, soils, land use, elevation, and species assemblages for >2100 counties east of the 100th meridian. Forest Inventory Analysis (FIA) data for >100 000 forested plots in the East provided the tree species range and abundance information for the trees. RTA was used to devise prediction rules from current species-environment relationships, which were then used to replicate the current distribution as well as predict the future potential distributions under two scenarios of climate change with twofold increases in the level of atmospheric CO2. Validation measures prove the utility of the RTA modeling approach for mapping current tree importance values across large areas, leading to increased confidence in the predictions of potential future species distributions. With our analysis of potential effects, we show that roughly 30 species could expand their range and/or weighted importance at least 10%, while an additional 30 species could decrease by at least 10%, following equilibrium after a changed climate. Depending on the global change scenario used, 4-9 species would potentially move out of the United States to the north. Nearly half of the species assessed (36 out of 80) showed the potential for the ecological optima to shift at least 100 km to the north, including seven that could move >250 km. Given these potential future distributions, actual species redistributions will be controlled by migration rates possible through fragmented landscapes.
Cited By (since 1996):56, Export Date: 26 November 2013, Source: Scopus
Tropical South America vegetation cover projections for the end of the
century differ considerably depending on climate scenario and also on
how physiological processes are considered in vegetation models. In this
paper we use a potential vegetation model (CPTEC-PVM2) to analyze biome
distribution in tropical South America under a range of climate
projections and a range of estimates about the effects of increased
atmospheric CO2. We show that if the CO2
"fertilization effect" indeed takes place and is maintained in the long
term in tropical forests, then it will avoid biome shifts in Amazonia in
most of the climate scenarios, even if the effect of CO2
fertilization is halved. However, if CO2 fertilization does
not play any important role on tropical forests in the future or if dry
season is longer than 4 months (projected by 2/14 GCMs), then there is
replacement of large portions of Amazonia by tropical savanna.
Recent attempts at projecting climate change impacts on biodiversity have used the IUCN Red List Criteria to obtain estimates of extinction rates based on projected range shifts. In these studies, the Criteria are often misapplied, potentially introducing substantial bias and uncertainty. These misapplications include arbitrary changes to temporal and spatial scales; confusion of the spatial variables; and assume a linear relationship between abundance and range area. Using the IUCN Red List Criteria to identify which species are threatened by climate change presents special problems and uncertainties, especially for shorter-lived species. Responses of most species to future climate change are not understood well enough to estimate extinction risks based solely on climate change scenarios and projections of shifts and/or reductions in range areas. One way to further such understanding would be to analyze the interactions among habitat shifts, landscape structure and demography for a number of species, using a combination of models. Evaluating the patterns in the results might allow the development of guidelines for assigning species to threat categories, based on a combination of life history parameters, characteristics of the landscapes in which they live, and projected range changes.
Tropical coral reef teleosts are exclusively ectotherms and their capacity for physical and physiological performance is therefore directly influenced by ambient temperature. This study examined the effect of increased water temperature to 3 °C above ambient on the swimming and metabolic performance of 10 species of damselfishes (Pomacentridae) representing evolutionary lineages from two subfamilies and four genera. Five distinct performance measures were tested: (a) maximum swimming speed (Ucrit), (b) gait-transition speed (the speed at which they change from strictly pectoral to pectoral-and-caudal swimming, Up−c), (c) maximum aerobic metabolic rate (MO2−MAX), (d) resting metabolic rate (MO2−REST), and (e) aerobic scope (ratio of MO2−MAX to MO2−REST, ASC). Relative to the control (29 °C), increased temperature (32 °C) had a significant negative effect across all performance measures examined, with the magnitude of the effect varying greatly among closely related species and genera. Specifically, five species spanning three genera (Dascyllus, Neopomacentrus and Pomacentrus) showed severe reductions in swimming performance with Ucrit reduced in these species by 21.3–27.9% and Up−c by 32.6–51.3%. Furthermore, five species spanning all four genera showed significant reductions in metabolic performance with aerobic scope reduced by 24.3–64.9%. Comparisons of remaining performance capacities with field conditions indicate that 32 °C water temperatures will leave multiple species with less swimming capacity than required to overcome the water flows commonly found in their respective coral reef habitats. Consequently, unless adaptation is possible, significant loss of species may occur if ocean warming of ≥3 °C arises.
We investigated whether the inclusion of topographical heterogeneity in bioclimatic envelope models would significantly alter predictions of climate change – induced broad-scale butterfly species range size changes in Europe. Using generalized additive models, and data on current climate and species distributions and two different climate scenarios (HadCM3A2 and HadCM3B2) for the period 2051–2080, we developed predictions of the currently suitable area and potential range size changes of 100 European butterfly species. The inclusion of elevation range increased the predictive accuracy of climate-only models for 86 of the 100 species. The differences in projected future distributions were most notable in mountainous areas, where the climate–topography models projected only ca. half of the species losses than the climate-only models. By contrast, climate–topography models estimated double the losses of species than climate-only models in the flatlands regions. Our findings suggest that disregarding topographical heterogeneity may cause a significant source of error in broad-scale bioclimatic modelling. Mountainous regions are likely to be even more important for future conservation of species than had until now been predicted, based on bioclimatic envelope models that did not take an explicit account of elevational range of grid squares.
An important issue in evolutionary biology is understanding the pattern of G matrix variation in natural populations. We estimated four G matrices based on the morphological traits of two cricket species, Gryllus firmus and G. pennsylvanicus, each reared in two environments. We used three matrix comparison approaches, including the Flury hierarchy, to improve our ability to perceive all aspects of matrix variation. Our results demonstrate that different methods perceive different aspects of the matrices, which suggests that, until more is known about these methods, future studies should use several different statistical approaches. We also found that the differences in G matrices within a species can be larger than the differences between species. We conclude that the expression of the genetic architecture can vary with the environment and that future studies should compare G matrices across several environments. We also conclude that G matrices can be conserved at the level of closely related species.
Reductions in river discharge (water availability) like those from climate change or increased water withdrawal, reduce freshwater biodiversity. We combined two scenarios from the Intergovernmental Panel for Climate Change with a global hydrological model to build global scenarios of future losses in river discharge from climate change and increased water withdrawal. Applying these results to known relationships between fish species and discharge, we build scenarios of losses (at equilibrium) of riverine fish richness. In rivers with reduced discharge, up to 75% (quartile range 4–22%) of local fish biodiversity would be headed toward extinction by 2070 because of combined changes in climate and water consumption. Fish loss in the scenarios fell disproportionately on poor countries. Reductions in water consumption could prevent many of the extinctions in these scenarios.
Aim There has been considerable recent interest in modelling the potential distributions of invasive species. However, research has developed in two opposite directions: the first, focusing on screening, utilizes phenomenological models; the second, focusing on predictions of invasion dynamics, utilizes mechanistic models. Here, we present hybrid modelling as an approach to bridge the gap and to integrate the advantages of both research directions.
Location Global.
Methods First, we briefly summarize the characteristics and limitations of both approaches (screening vs . understanding). Then, we review the recent developments of hybrid models, discuss their current problems and offer suggestions to improve them.
Results Generally, hybrid models are able to combine the advantages of currently used phenomenological and mechanistic approaches. Main challenges in building hybrid models are the choices of the appropriate degree of detail and efficiency and the decision on how to connect the different sub‐models. Given these challenges, we discuss the links between the phenomenological and the mechanistic model parameters, the underlying concepts of fundamental and realized niches and the problem of feedback loops between population dynamics and environmental factors.
Main conclusions Once the above challenges have been addressed and the necessary framework has been developed, hybrid models will provide outstanding tools for overcoming past limitations and will provide the means to make reliable and robust predictions of the potential distribution of invasive species, their population dynamics and the potential outcomes of the overall invasion process.
The rapidly increasing atmospheric concentrations of greenhouse gases may lead to significant changes in regional and seasonal climate patterns. Such changes can strongly influence the diversity and distribution of species and, therefore, affect ecosystems and biodiversity. To assess these changes we developed a model, called euromove. The model uses climate data from 1990 to 2050 as compiled from the image 2 model, and determines climate envelopes for about 1400 plant species by multiple logistic regression analysis. The climate envelopes were applied to the projected climate to obtain predictions about plant diversity and distributions by 2050. For each European grid cell, euromove calculates which species would still occur in forecasted future climate conditions and which not. The results show major changes in biodiversity by 2050. On average, 32% of the European plant species that were present in a cell in 1990 would disappear from that cell. The area, in which 32% or more of the 1990 species will disappear, takes up 44% of the modelled European area. Individual responses of the plant species to the forecasted climate change were diverse. In reviewing possible future trends, we found that plant species, in general, would find their current climate envelopes further northeast by 2050, shifting ranges that were comparable with those ranges in other studies.
Aim Robust and reliable predictions of the effects of climate change on biodiversity are required in formulating conservation and management strategies that best retain biodiversity into the future. Significant challenges in modelling climate change impacts arise from limitations in our current knowledge of biodiversity. Community-level modelling can complement species-level approaches in overcoming these limitations and predicting climate change impacts on biodiversity as a whole. However, the community-level approaches applied to date have been largely correlative, ignoring the key processes that influence change in biodiversity over space and time. Here, we suggest that the development of new ‘semi-mechanistic’ community-level models would substantially increase our capacity to predict climate change impacts on biodiversity.
Location Global.
Methods Drawing on an expansive review of biodiversity modelling approaches and recent advances in semi-mechanistic modelling at the species level, we outline the main elements of a new semi-mechanistic community-level modelling approach.
Results Our quantitative review revealed a sharp divide between mechanistic and non-mechanistic biodiversity modelling approaches, with very few semi-mechanistic models developed to date.
Main conclusions We suggest that the conceptual framework presented here for combining mechanistic and non-mechanistic community-level approaches offers a promising means of incorporating key processes into predictions of climate change impacts on biodiversity whilst working within the limits of our current knowledge.
We use a physically plausible four parameter linear response equation to relate 2,000years of global temperatures and sea
level. We estimate likelihood distributions of equation parameters using Monte Carlo inversion, which then allows visualization
of past and future sea level scenarios. The model has good predictive power when calibrated on the pre-1990 period and validated
against the high rates of sea level rise from the satellite altimetry. Future sea level is projected from intergovernmental
panel on climate change (IPCC) temperature scenarios and past sea level from established multi-proxy reconstructions assuming
that the established relationship between temperature and sea level holds from 200 to 2100 ad. Over the last 2,000years minimum sea level (−19 to −26cm) occurred around 1730 ad, maximum sea level (12–21cm) around 1150 ad. Sea level 2090–2099 is projected to be 0.9 to 1.3m for the A1B scenario, with low probability of the rise being within
IPCC confidence limits.
Abstract This study tests the ability of five Dynamic Global Vegetation Models (DGVMs), forced with observed climatology and atmospheric CO2, to model the contemporary global carbon cycle. The DGVMs are also coupled to a fast ‘climate analogue model’, based on the Hadley Centre General Circulation Model (GCM), and run into the future for four Special Report Emission Scenarios (SRES): A1FI, A2, B1, B2. Results show that all DGVMs are consistent with the contemporary global land carbon budget. Under the more extreme projections of future environmental change, the responses of the DGVMs diverge markedly. In particular, large uncertainties are associated with the response of tropical vegetation to drought and boreal ecosystems to elevated temperatures and changing soil moisture status. The DGVMs show more divergence in their response to regional changes in climate than to increases in atmospheric CO2 content. All models simulate a release of land carbon in response to climate, when physiological effects of elevated atmospheric CO2 on plant production are not considered, implying a positive terrestrial climate-carbon cycle feedback. All DGVMs simulate a reduction in global net primary production (NPP) and a decrease in soil residence time in the tropics and extra-tropics in response to future climate. When both counteracting effects of climate and atmospheric CO2 on ecosystem function are considered, all the DGVMs simulate cumulative net land carbon uptake over the 21st century for the four SRES emission scenarios. However, for the most extreme A1FI emissions scenario, three out of five DGVMs simulate an annual net source of CO2 from the land to the atmosphere in the final decades of the 21st century. For this scenario, cumulative land uptake differs by 494 Pg C among DGVMs over the 21st century. This uncertainty is equivalent to over 50 years of anthropogenic emissions at current levels.
The rich biodiversity of southern Africa has to date been relatively unimpacted by the activities of modern society, but to what degree will this situation persist into the 21st century? We use a leading global environmental assessment model (IMAGE) to explore future land use and climate change in southern Africa under the scenarios developed by the Millennium Ecosystem Assessment. We assess the impacts on terrestrial biodiversity using the Biodiversity Intactness Index, which gives the average change in population size relative to the pre-modern state, across all terrestrial species of plants and vertebrates. Over the coming century, we project absolute declines in the average population sizes of these taxa that are two to three times greater than the reductions that have occurred since circa 1700. Our results highlight the immense challenges faced by efforts to reduce rates of biodiversity loss in southern Africa, even under relatively optimistic scenarios. These results stress the urgent need for better aligning biodiversity conservation and development priorities in the region. Furthermore, we suggest that context-sensitive conservation targets that account for the development imperatives in different parts of the region are needed.
Given the rate of projected environmental change for the 21st century, urgent adaptation and mitigation measures are required to slow down the on-going erosion of biodiversity. Even though increasing evidence shows that recent human-induced environmental changes have already triggered species’ range shifts, changes in phenology and species’ extinctions, accurate projections of species’ responses to future environmental changes are more difficult to ascertain. This is problematic, since there is a growing awareness of the need to adopt proactive conservation planning measures using forecasts of species’ responses to future environmental changes.
Organisms live in an ever-changing world. Most of evolutionary theory considers one solution to this problem: population-level adaptation. In fact, empirical studies have revealed an enormous variety of mechanisms to cope with environmental fluctuations. Some organisms use behavioral or physiological modifications that leave no permanent trace in the genes of future generations. Others withstand environmental change through the regular production of diverse offspring, in which the diversity can be either genetic or nongenetic. Evolutionary theorists now have the opportunity to catch up with the empirical evolutionary biology, and to integrate the diverse forms of ‘adaptive variation’ into a single conceptual framework. Here, we propose a classification according to the level at which the adaptive variation occurs and discuss some of the mechanisms underlying the variation. This perspective unites independent lines of research in molecular biology, microbiology, macroevolution, ecology, immunology and neurobiology, and suggests directions for a more comprehensive theory of adaptive variation.
We explored impacts of climate change on the geographic distribution of European beech by applying state of the art statistical and process-based models, and assessed possible climate change impacts on both adaptive capacity in the centre of its distribution and adaptive responses of functional traits at the leading and trailing edge of the current distribution. The species area models agree that beech has the potential to expand its northern edge and loose habitat at the southern edge of its distribution in a future climate. The change in local population size in the centre of the distribution of beech has a small effect on the genetic diversity of beech, which is projected to maintain its current population size or to increase in population size. Thus, an adaptive response of functional traits of small populations at the leading and trailing edges of the distribution is possible based on genetic diversity available in the local population, even within a period of 2–3 generations.We conclude that the adaptive responses of key functional traits should not be ignored in climate change impact assessment on beech. Adaptation to the local environment may lead to genetic and phenotypic structured populations over the species area already in few generations, depending on the forest management system applied. We recommend taking local differentiation into account in a future generation of process-based species area models.
Climate change and biological invasions are key processes affecting global biodiversity, yet their effects have usually been considered separately. Here, we emphasise that global warming has enabled alien species to expand into regions in which they previously could not survive and reproduce. Based on a review of climate-mediated biological invasions of plants, invertebrates, fishes and birds, we discuss the ways in which climate change influences biological invasions. We emphasise the role of alien species in a more dynamic context of shifting species' ranges and changing communities. Under these circumstances, management practices regarding the occurrence of 'new' species could range from complete eradication to tolerance and even consideration of the 'new' species as an enrichment of local biodiversity and key elements to maintain ecosystem services.